Abstract: Determination of the precise mode of action (MOA) for bioactive metabolites remains one of the central challenges facing the botanical natural products community. Because of the technical challenges associated with this issue, and the complex nature of botanicals and natural products extracts, MOA determination is often not addressed until late in the discovery process, leading to a high rate of redundancy and attrition for drug discovery applications. This TRD project aims to invert the traditional natural product discovery process by developing a new platform for the prediction of compound identities and modes of action directly from primary screening of complex mixtures. This approach takes advantage of recently developed phenotypic image-based screening developed in our laboratories for assessing biological activities of natural product extracts, and combines this with high-resolution uPLC-MS analyses to connect chemical constituents with unique but not predefined biological phenotypes. By using the integration of these two information-rich orthogonal profiling methods we have been able to successfully demonstrate the de novo prediction of compound MOs, and validate these by downstream evaluation of pure compounds isolated using this methodology. This TRD project aims to 1) increase the resolution of the biological assay through the inclusion of additional cell lines, stain sets and reference compounds, 2) Develop a next-generation untargeted metabolomics platform specifically optimized for the analysis of natural product mixtures, and 3) Create new informatics tools to integrate and query these two information-rich profiling methods. At the conclusion of the project it is anticipated that we will have created a unique tool with broad utility within the botanical natural products field, which is accessible via a web interface and is configured for facile inclusion of samples and extracts from all interested researchers both nationally and internationally.